Gravity-based particle swarm optimization with hybrid cooperative swarm approach for global optimization

Ying Loong Lee, Ayman A. El-Saleh, Mahamod Ismail

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Premature convergence has been recognized as one of the major drawbacks of particle swarm optimization (PSO) algorithms. In particular, the lack of diversity in PSO performance is an essential cause that commonly results in high susceptibility to prematurely converge to local optima especially in complex multimodal problems with high dimensionality. This paper presents a new PSO operational strategy based on gravity concept to address the aforementioned drawback and it is named as gravity-based particle swarm optimizer (GPSO). In addition, GPSO is further modified by adopting the cooperation concept of the conventional cooperative particle swarm optimizer (CPSO) to develop an extended version of GPSO called cooperative gravity-based particle swarm optimizer (CGPSO). Simulation results manifest that CGPSO performs satisfactorily on unimodal functions while it generally performs better on multimodal functions than GPSO and other conventional PSO variants. Finally, the proposed GPSO and CGPSO are applied into the problem of optimizing the detection performance of soft decision fusion for cooperative spectrum sensing in cognitive radio networks. For this problem, computer simulations show that the proposed CGPSO outperforms all other PSO variants in terms of quality of solutions whereas GPSO is found to be the best when the computational cost is taken into account.

Original languageEnglish
Pages (from-to)465-481
Number of pages17
JournalJournal of Intelligent and Fuzzy Systems
Volume26
Issue number1
DOIs
Publication statusPublished - 2014

Fingerprint

Particle Swarm Optimizer
Global optimization
Swarm
Global Optimization
Particle swarm optimization (PSO)
Particle Swarm Optimization
Gravity
Gravitation
Decision Fusion
Multimodal Function
Spectrum Sensing
Premature Convergence
Cognitive Radio Networks
Cognitive radio
Particle Swarm Optimization Algorithm
Susceptibility
Dimensionality
Computational Cost
Fusion reactions
Computer Simulation

Keywords

  • CGPSO
  • Continuous PSO
  • Cooperative swarms
  • GPSO
  • Optimization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Engineering(all)
  • Statistics and Probability

Cite this

Gravity-based particle swarm optimization with hybrid cooperative swarm approach for global optimization. / Lee, Ying Loong; El-Saleh, Ayman A.; Ismail, Mahamod.

In: Journal of Intelligent and Fuzzy Systems, Vol. 26, No. 1, 2014, p. 465-481.

Research output: Contribution to journalArticle

Lee, Ying Loong ; El-Saleh, Ayman A. ; Ismail, Mahamod. / Gravity-based particle swarm optimization with hybrid cooperative swarm approach for global optimization. In: Journal of Intelligent and Fuzzy Systems. 2014 ; Vol. 26, No. 1. pp. 465-481.
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